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Maier SH, Schönecker S, Anagnostatou V, Garny S, Nitschmann A, Fleischmann DF, Büttner M, Kaul D, Imhoff D, Fokas E, Seidel C, Hau P, Kölbl O, Popp I, Grosu AL, Haussmann J, Budach W, Celik E, Kahl KH, Hoffmann E, Tabatabai G, Paulsen F, Holzgreve A, Albert NL, Mansmann U, Corradini S, Belka C, Niyazi M, Bodensohn R. Dummy run for planning of isotoxic dose-escalated radiation therapy for glioblastoma used in the PRIDE trial (NOA-28; ARO-2024-01; AG-NRO-06). Clin Transl Radiat Oncol 2024; 47:100790. [PMID: 38765202 PMCID: PMC11101689 DOI: 10.1016/j.ctro.2024.100790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 05/02/2024] [Accepted: 05/02/2024] [Indexed: 05/21/2024] Open
Abstract
Background The PRIDE trial (NOA-28; ARO-2024-01; AG-NRO-06; NCT05871021) is designed to determine whether a dose escalation with 75.0 Gy in 30 fractions can enhance the median overall survival (OS) in patients with methylguanine methyltransferase (MGMT) promotor unmethylated glioblastoma compared to historical median OS rates, while being isotoxic to historical cohorts through the addition of concurrent bevacizumab (BEV). To ensure protocol-compliant irradiation planning with all study centers, a dummy run was planned and the plan quality was evaluated. Methods A suitable patient case was selected and the computed tomography (CT), magnetic resonance imaging (MRI) and O-(2-[18F]fluoroethyl)-L-tyrosine (FET) positron emission tomography (PET) contours were made available. Participants at the various intended study sites performed radiation planning according to the PRIDE clinical trial protocol. The treatment plans and dose grids were uploaded as Digital Imaging and Communications in Medicine (DICOM) files to a cloud-based platform. Plan quality and protocol adherence were analyzed using a standardized checklist, scorecards and indices such as Dice Score (DSC) and Hausdorff Distance (HD). Results Median DSC was 0.89, 0.90, 0.88 for PTV60, PTV60ex (planning target volume receiving 60.0 Gy for the standard and the experimental plan, respectively) and PTV75 (PTV receiving 75.0 Gy in the experimental plan), respectively. Median HD values were 17.0 mm, 13.9 mm and 12.1 mm, respectively. These differences were also evident in the volumes: The PTV60 had a volume range of 219.1-391.3 cc (median: 261.9 cc) for the standard plans, while the PTV75 volumes for the experimental plans ranged from 71.5-142.7 cc (median: 92.3 cc). The structures with the largest deviations in Dice score were the pituitary gland (median 0.37, range 0.00-0.69) and the right lacrimal gland (median 0.59, range 0.42-0.78). Conclusions The deviations revealed the necessity of systematic trainings with appropriate feedback before the start of clinical trials in radiation oncology and the constant monitoring of protocol compliance throw-out the study. Trial registration NCT05871021.
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Affiliation(s)
- Sebastian H. Maier
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
- Bavarian Cancer Research Center (BZKF), Munich, Germany
| | - Stephan Schönecker
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
- Bavarian Cancer Research Center (BZKF), Munich, Germany
| | - Vasiliki Anagnostatou
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
- Bavarian Cancer Research Center (BZKF), Munich, Germany
| | - Sylvia Garny
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Alexander Nitschmann
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Daniel F. Fleischmann
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
- German Cancer Consortium (DKTK), partner site Munich, a partnership between DKFZ and LMU University Hospital, Munich, Germany
- German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Marcel Büttner
- Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany
| | - David Kaul
- Department of Radiation Oncology and Radiotherapy, Charité-Universitätsmedizin Berlin (Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health), Berlin, Germany
| | - Detlef Imhoff
- Department of Radiotherapy of Oncology, University of Frankfurt, Frankfurt, Germany
| | - Emmanouil Fokas
- Department of Radiotherapy of Oncology, University of Frankfurt, Frankfurt, Germany
- Department of Radiation Oncology, CyberKnife and Radiation Therapy, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
| | - Clemens Seidel
- Department of Radiation Oncology, University Hospital Leipzig, University of Leipzig, Leipzig, Germany
| | - Peter Hau
- Department of Neurology and Wilhelm Sander-NeuroOncology Unit, Regensburg University Hospital, Regensburg, Germany
| | - Oliver Kölbl
- Department of Radiotherapy, University Medical Center Regensburg, Regensburg, Germany
| | - Ilinca Popp
- Department of Radiation Oncology, University of Freiburg Faculty of Medicine, Freiburg, Germany
| | - Anca-Ligia Grosu
- Department of Radiation Oncology, University of Freiburg Faculty of Medicine, Freiburg, Germany
| | - Jan Haussmann
- Department of Radiation Oncology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
| | - Wilfried Budach
- Department of Radiation Oncology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
| | - Eren Celik
- Department of Radiation Oncology, CyberKnife and Radiation Therapy, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
- Dept. of Radiation Oncology, Faculty of Medicine and University Hospital Ruhr-University Bochum, Marien Hospital Herne, Herne, Germany
| | - Klaus-Henning Kahl
- Department of Radiooncology, University Hospital Augsburg, Augsburg, Germany
| | - Elgin Hoffmann
- Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Tübingen, Germany
| | - Ghazaleh Tabatabai
- Department of Neurology and Interdisciplinary Neuro-Oncology, University Hospital Tübingen, Hertie Institute for Clinical Brain Research, Tübingen, Germany
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Tübingen, Germany
| | - Frank Paulsen
- Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Tübingen, Germany
| | - Adrien Holzgreve
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
- Ahmanson Translational Theranostics Division, David Geffen School of Medicine, University of California Los Angeles (UCLA), Los Angeles, USA
| | - Nathalie L. Albert
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - Ulrich Mansmann
- Institute for Medical Information Processing, Biometry and Epidemiology, Faculty of Medicine, LMU Munich, Munich, Germany
| | - Stefanie Corradini
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Claus Belka
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
- Bavarian Cancer Research Center (BZKF), Munich, Germany
- German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Maximilian Niyazi
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
- Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Tübingen, Germany
- German Cancer Consortium (DKTK), partner site Tübingen, a partnership between DKFZ and University Hospital Tübingen, Tübingen, Germany
| | - Raphael Bodensohn
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
- Department of Radiation Oncology, University Hospital Tübingen, Tübingen, Germany
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Tübingen, Germany
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Feygelman V, Latifi K, Bowers M, Greco K, Moros EG, Isacson M, Angerud A, Caudell J. Maintaining dosimetric quality when switching to a Monte Carlo dose engine for head and neck volumetric-modulated arc therapy planning. J Appl Clin Med Phys 2022; 23:e13572. [PMID: 35213089 PMCID: PMC9121035 DOI: 10.1002/acm2.13572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 02/06/2022] [Accepted: 02/08/2022] [Indexed: 11/13/2022] Open
Abstract
Head and neck cancers present challenges in radiation treatment planning due to the large number of critical structures near the target(s) and highly heterogeneous tissue composition. While Monte Carlo (MC) dose calculations currently offer the most accurate approximation of dose deposition in tissue, the switch to MC presents challenges in preserving the parameters of care. The differences in dose‐to‐tissue were widely discussed in the literature, but mostly in the context of recalculating the existing plans rather than reoptimizing with the MC dose engine. Also, the target dose homogeneity received less attention. We adhere to strict dose homogeneity objectives in clinical practice. In this study, we started with 21 clinical volumetric‐modulated arc therapy (VMAT) plans previously developed in Pinnacle treatment planning system. Those plans were recalculated “as is” with RayStation (RS) MC algorithm and then reoptimized in RS with both collapsed cone (CC) and MC algorithms. MC statistical uncertainty (0.3%) was selected carefully to balance the dose computation time (1–2 min) with the planning target volume (PTV) dose‐volume histogram (DVH) shape approaching that of a “noise‐free” calculation. When the hot spot in head and neck MC‐based treatment planning is defined as dose to 0.03 cc, it is exceedingly difficult to limit it to 105% of the prescription dose, as we were used to with the CC algorithm. The average hot spot after optimization and calculation with RS MC was statistically significantly higher compared to Pinnacle and RS CC algorithms by 1.2 and 1.0 %, respectively. The 95% confidence interval (CI) observed in this study suggests that in most cases a hot spot of ≤107% is achievable. Compared to the 95% CI for the previous clinical plans recalculated with RS MC “as is” (upper limit 108%), in real terms this result is at least as good or better than the historic plans.
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Affiliation(s)
- Vladimir Feygelman
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, Florida, USA
| | - Kujtim Latifi
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, Florida, USA
| | - Mark Bowers
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, Florida, USA
| | - Kevin Greco
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, Florida, USA
| | - Eduardo G Moros
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, Florida, USA
| | - Max Isacson
- RaySearch Laboratories AB, Stockholm, Sweden
| | | | - Jimmy Caudell
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, Florida, USA
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